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SCENARIO 14-6
One of the Most Common Questions of Prospective β\beta

question 79

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SCENARIO 14-6
One of the most common questions of prospective house buyers pertains to the cost of heating in dollars (Y) . To provide its customers with information on that matter, a large real estate firm used the following 2 variables to predict heating costs: the daily minimum outside temperature in degrees of Fahrenheit ( X1 ) and the amount of insulation in inches ( X 2 ) . Given below is EXCEL output of the regression model.
SCENARIO 14-6 One of the most common questions of prospective house buyers pertains to the cost of heating in dollars (Y) . To provide its customers with information on that matter, a large real estate firm used the following 2 variables to predict heating costs: the daily minimum outside temperature in degrees of Fahrenheit ( X<sub>1</sub> ) and the amount of insulation in inches ( X <sub>2</sub> ) . Given below is EXCEL output of the regression model. Also SSR (X<sub>1</sub> | X<sub>2</sub>) = 8343.3572 and SSR (X<sub>2</sub> | X<sub>1</sub>) = 4199.2672 -Referring to Scenario 14-6 and allowing for a 1% probability of committing a type I error,what is the decision and conclusion for the test H<sub>0 </sub>: \beta <sub>1 </sub>=0 \beta <sub>2 </sub>= 0 vs. H<sub>1 </sub>: At least one \beta <sub>j </sub> \neq 0,j = 1,2 <sup>?</sup> A) Do not reject H<sub>0</sub> and conclude that the 2 independent variables taken as a group have significant linear effects on heating costs. B) Do not reject H<sub>0</sub> and conclude that the 2 independent variables taken as a group do not have significant linear effects on heating costs. C) Reject H<sub>0</sub> and conclude that the 2 independent variables taken as a group have significant linear effects on heating costs. D) Reject H<sub>0</sub> and conclude that the 2 independent variables taken as a group do not have significant linear effects on heating costs.
SCENARIO 14-6 One of the most common questions of prospective house buyers pertains to the cost of heating in dollars (Y) . To provide its customers with information on that matter, a large real estate firm used the following 2 variables to predict heating costs: the daily minimum outside temperature in degrees of Fahrenheit ( X<sub>1</sub> ) and the amount of insulation in inches ( X <sub>2</sub> ) . Given below is EXCEL output of the regression model. Also SSR (X<sub>1</sub> | X<sub>2</sub>) = 8343.3572 and SSR (X<sub>2</sub> | X<sub>1</sub>) = 4199.2672 -Referring to Scenario 14-6 and allowing for a 1% probability of committing a type I error,what is the decision and conclusion for the test H<sub>0 </sub>: \beta <sub>1 </sub>=0 \beta <sub>2 </sub>= 0 vs. H<sub>1 </sub>: At least one \beta <sub>j </sub> \neq 0,j = 1,2 <sup>?</sup> A) Do not reject H<sub>0</sub> and conclude that the 2 independent variables taken as a group have significant linear effects on heating costs. B) Do not reject H<sub>0</sub> and conclude that the 2 independent variables taken as a group do not have significant linear effects on heating costs. C) Reject H<sub>0</sub> and conclude that the 2 independent variables taken as a group have significant linear effects on heating costs. D) Reject H<sub>0</sub> and conclude that the 2 independent variables taken as a group do not have significant linear effects on heating costs.
SCENARIO 14-6 One of the most common questions of prospective house buyers pertains to the cost of heating in dollars (Y) . To provide its customers with information on that matter, a large real estate firm used the following 2 variables to predict heating costs: the daily minimum outside temperature in degrees of Fahrenheit ( X<sub>1</sub> ) and the amount of insulation in inches ( X <sub>2</sub> ) . Given below is EXCEL output of the regression model. Also SSR (X<sub>1</sub> | X<sub>2</sub>) = 8343.3572 and SSR (X<sub>2</sub> | X<sub>1</sub>) = 4199.2672 -Referring to Scenario 14-6 and allowing for a 1% probability of committing a type I error,what is the decision and conclusion for the test H<sub>0 </sub>: \beta <sub>1 </sub>=0 \beta <sub>2 </sub>= 0 vs. H<sub>1 </sub>: At least one \beta <sub>j </sub> \neq 0,j = 1,2 <sup>?</sup> A) Do not reject H<sub>0</sub> and conclude that the 2 independent variables taken as a group have significant linear effects on heating costs. B) Do not reject H<sub>0</sub> and conclude that the 2 independent variables taken as a group do not have significant linear effects on heating costs. C) Reject H<sub>0</sub> and conclude that the 2 independent variables taken as a group have significant linear effects on heating costs. D) Reject H<sub>0</sub> and conclude that the 2 independent variables taken as a group do not have significant linear effects on heating costs.
Also SSR (X1 | X2) = 8343.3572 and SSR (X2 | X1) = 4199.2672
-Referring to Scenario 14-6 and allowing for a 1% probability of committing a type I error,what is the decision and conclusion for the test
H0 : β\beta 1 =0 β\beta 2 = 0 vs. H1 : At least one β\beta j ≠\neq 0,j = 1,2 ?

Definitions:

Utility Function

A mathematical representation of how a consumer's satisfaction or happiness is affected by consuming different quantities of goods and services.

Golf

A sport involving hitting a small ball into a series of holes with the least number of strokes possible, using various clubs.

Tennis

A racket sport that can be played individually against a single opponent or between two teams of two players each, where players hit a ball over a net trying to score points against opponents.

Curds

Soft, white substance formed when milk coagulates, used as the basis for cheese making or eaten directly as a food product.

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